OffLadder

Check career change facts with sources

check_career_change_facts

Read-onlyIdempotent

Answers factual questions about changing jobs or careers, e.g. 'is it too late to change careers at 40', 'is 50 too old to switch careers', 'how many jobs does the average person have in a lifetime', 'how long do people stay with one employer', 'how many different careers are there', 'will AI make my skills outdated', 'how fast are job skills changing'. Returns exact quotes from primary sources (U.S. Bureau of Labor Statistics, O*NET, World Economic Forum) with links, or says plainly that no checked figure exists. Never returns an estimate.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "question": "<question>"
    },
    "name": "check_career_change_facts"
  }
}

Input Schema

Name	Required	Description	Default
`question`	Yes	The person's question, in their words.

Output Schema

Name	Required	Description
`facts`	Yes
`cta_label`	Yes	A short label for that link.
`start_url`	Yes	OffLadder's short onboarding, with a starting world picked if one was clear.
`exact_match`	Yes	False when OffLadder holds no checked figure for the question.
`continue_url`	Yes	The same link, as the suggested next step.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, non-destructive, and openWorldHint=false, so the safety profile is covered. The description adds genuine behavioral context beyond that: it names the three source providers, promises verbatim quotes with links, and states the failure mode ('says plainly that no checked figure exists') and a hard constraint ('never returns an estimate'). That is useful, though the output schema already carries the return shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose and the sourcing guarantee are front-loaded, and every sentence carries information. The seven-item example list is slightly long and could be trimmed to three or four without losing signal, but the examples do real work in delimiting scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter, read-only, non-open-world lookup tool with an output schema, nothing material is missing. The description covers what it answers, what source corpus it uses, what the return looks like, and what happens when no figure exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single parameter is documented with its own description ('The person's question, in their words'), so the baseline is 3. The example questions in the description do help calibrate what kinds of phrasing are in scope, but no length, format, or phrasing constraints beyond the schema's minLength/maxLength are added.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource pair ('Answers factual questions about changing jobs or careers') and then anchors it with seven concrete example questions, so an agent can immediately tell this returns sourced statistics rather than narrative guidance like the sibling guide tools. The sourcing constraint ('exact quotes from primary sources ... or says plainly that no checked figure exists') further pins down the operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The example questions clearly delineate the class of query this tool handles (age-related career questions, lifetime job statistics, skills obsolescence), giving strong implicit usage guidance. It stops short of explicit routing guidance such as 'use browse_career_guides for narrative advice instead' or stating what question types are out of scope.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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